1 code implementation • 12 Dec 2023 • Jenny Hamer, Eleni Triantafillou, Bart van Merriënboer, Stefan Kahl, Holger Klinck, Tom Denton, Vincent Dumoulin
The ability for a machine learning model to cope with differences in training and deployment conditions--e. g. in the presence of distribution shift or the generalization to new classes altogether--is crucial for real-world use cases.
1 code implementation • 12 Jul 2023 • Burooj Ghani, Tom Denton, Stefan Kahl, Holger Klinck
With the advent of deep learning models, classification of important signals from these datasets has markedly improved.
1 code implementation • 5 Apr 2023 • Pu Li, Marie Roch, Holger Klinck, Erica Fleishman, Douglas Gillespie, Eva-Marie Nosal, Yu Shiu, Xiaobai Liu
To overcome this limitation, we present a framework of stage-wise generative adversarial networks (GANs), which compile new whistle data suitable for deep model training via three stages: generation of background noise in the spectrogram, generation of whistle contours, and generation of whistle signals.
no code implementations • 25 Oct 2021 • Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie W. Mathis, Frank van Langevelde, Tilo Burghardt, Roland Kays, Holger Klinck, Martin Wikelski, Iain D. Couzin, Grant van Horn, Margaret C. Crofoot, Charles V. Stewart, Tanya Berger-Wolf
Data acquisition in animal ecology is rapidly accelerating due to inexpensive and accessible sensors such as smartphones, drones, satellites, audio recorders and bio-logging devices.
no code implementations • 20 Aug 2021 • Irina Tolkova, Brian Chu, Marcel Hedman, Stefan Kahl, Holger Klinck
Monitoring of bird populations has played a vital role in conservation efforts and in understanding biodiversity loss.
no code implementations • 1 Nov 2019 • Vincent Lostanlen, Kaitlin Palmer, Elly Knight, Christopher Clark, Holger Klinck, Andrew Farnsworth, Tina Wong, Jason Cramer, Juan Pablo Bello
This paper proposes to perform unsupervised detection of bioacoustic events by pooling the magnitudes of spectrogram frames after per-channel energy normalization (PCEN).
1 code implementation • 6 Jun 2019 • Dena J. Clink, Holger Klinck
The recent improvements in recording technology, data storage and battery life have led to an increased interest in the use of passive acoustic monitoring for a variety of research questions.
3 code implementations • 19 Apr 2018 • Stefan Kahl, Thomas Wilhelm-Stein, Holger Klinck, Danny Kowerko, Maximilian Eibl
Reliable identification of bird species in recorded audio files would be a transformative tool for researchers, conservation biologists, and birders.